首页 /研究 /Deep Reinforcement Learning for Machine Scheduling: Methodology, the State-of-The-Art, and Future Directions

LEARNING

Deep Reinforcement Learning for Machine Scheduling: Methodology, the State-of-The-Art, and Future Directions

Maziyar Khadivi, Todd Charter, Marjan Yaghoubi, Masoud Jalayer, Maryam Ahang, Ardeshir Shojaeinasab, Homayoun Najjaran

发表年份: 2023
引用次数: 15

关键词

Reinforcement learningComputer scienceArtificial intelligenceScheduling (production processes)Machine learningOperations researchEngineeringOperations management

Deep Reinforcement Learning for Machine Scheduling: Methodology, the State-of-The-Art, and Future Directions

关键词

相关论文

Statistical Learning Theory

Artificial intelligence: a modern approach

Applied Nonlinear Control

A new optimizer using particle swarm theory